Guide: Data Masking

The Fundamentals of Data Redaction

The value of data isn’t lost on anyone. Be it small businesses or large corporations, every organization needs data in order to monitor their performance, have a look at their competitors’ business, identify loopholes or weaknesses, and also decide how you can expand or improve your operations. Along with this data also comes a ton of responsibility to keep it secure, which is something that keeps data managers and security experts up all night.

There are several types of businesses in which there is a need to store and process sensitive information, particularly when it comes to personally identifiable information (PII). This refers to information that can be used to identify a person, directly or indirectly.

One of the best ways to do so is through data redaction, which is one of the most effective methods in data security. It can be just what you need to safeguard your company from a data breach, which can hurt your credibility.

In this guide, you will learn:

This is a part of our comprehensive data masking guide.

What is Data Redaction?

Data redaction is a method used to protect sensitive data from being compromised or leaked. It involves the removal of particular pieces of data from the whole of it, in an effort to keep it from being exposed as a whole and used for malicious or nefarious purposes.

You might have heard the term ‘redacted information’ in movies or classified documentation where some of the information is blacked out. The same principle is applied in the process of data redaction.

Basically, this process breaks down data into various pieces of information, and removes or hides portions that can be used to identify or link to a particular person, company, or organization. For instance, if you have credit card information of your customers stored in your database, you may choose to redact the first names of all the cardholders, or the first and last four digits of the card numbers.

Data redaction tools are being used by companies all over the world in order to hide and protect their sensitive data. Not only does it help in keeping the data secure, but also preserves its integrity and authenticity.

Data Redaction vs Data Masking

If you are reading up on data redaction, you would also come across another term: data masking. Both of these are tools used in data security, but they have some basic differences among them.

While data redaction is the process of removing certain pieces of sensitive or personally identifiable information, data masking is a process in which sensitive and authentic information is replaced with inauthentic information that has the same structure.

Data masking is mostly used for creating sample data for testing or training purposes, so that any personally identifiable information or sensitive data isn’t exposed or manipulated during the production or testing phase in an organization. This method also keeps the data structure and data types intact, so that data can be used in applications.

On the other hand, data redaction is used to conceal personally identifiable or classified information from comprehendible data, so that any sensitive data doesn’t get leaked to the public.

Therefore, we can safely say that while data redaction is a method to ‘remove’ data, data masking is a method to ‘replace’ data with something in a similar format. In many cases, data redaction is considered to be a sub-type of data masking.

Can Redacted Data be Restored?

When you redact sensitive data, the specific portion of the information is actually removed to maintain data security. Naturally, this would compel you to think: Can redacted data be restored?

Earlier, people used to add a black box over sensitive information in Microsoft Word files and convert them to PDF. However, this meant that anyone with access to the Word file would be able to remove the black box and reveal the information underneath.

In the more advanced versions of PDF readers and even Word, you can’t retrieve information once it has been redacted, which makes it much more secure than the previous versions.

In essence, you can’t restore redacted data unless you have a copy of the original file with you, or you have some highly experienced and expert data engineers who can access the metadata and do it for you.

This is why data redaction is a highly effective and useful method for protecting sensitive data, but it also requires you to store your original data properly, so that no one can access it.

Benefits of Data Redaction

By this point, you are well aware of how data redaction works, and how it can be used to conceal sensitive and identifiable information from the public, as well as people with nefarious intentions. Let’s have a look at some of the benefits of doing so.

It Makes Data Usable

Regardless of which industry you belong to, you need to use data for your business operations. In some cases, you also have to make the data available to the public. By applying a data redaction policy, you will be able to desensitize the data, which makes it suitable for use without compromising on security. That’s true, of course, unless the redacted data is the data you need, in which case you should choose other anonymization options.

It Ensures Compliance

There are several data privacy and security regulations that have been implemented in the previous decade, owing to an increased number of breaches that are being experienced by companies across the world. By applying data redaction, companies are able to comply with these regulations.

It Helps Keep Data Secure

Another benefit of data redaction is that it helps you keep sensitive and valuable data intact and secure. As you may know already, there has been a significant increase in data breaches in the past few years, and it greatly hurts the credibility of organizations. Through data redaction, these issues can be avoided.

Static Vs Dynamic Redaction

There are two different approaches in data redaction: static and dynamic redaction.

Static Redaction

In static redaction, the data is copied or moved to a copy that already has redaction algorithms and measures. It can be used for redacting sensitive information from large amounts of data. It requires quite a lot of time and resources in order to do so.

Dynamic Redaction

Dynamic data redaction involves redacting sensitive information from data in real-time, which is why it is also known as data-in-transit redaction. For this process, the data doesn’t have to go through batch processing to be redacted. However, it is much more suitable for read-only applications, and also has significant performance overheads.

Summary

When designing a data privacy strategy, data redaction is often considered as a first step. You might be able to use it for securing the sensitive data of your business, and also to avoid any risk of data breaches or leaks.

Dynamic Data Redaction With Satori